Context

Reviews are a way to gain insight into a product/service. In machine learning tasks, text reviews play an important role in predicting/gaining insights. User-generated place reviews are extremely handy when it comes to choosing a neighborhood to live in. Niche has got a huge amount of review-rating for American neighborhood, which is perfect for several NLP tasks.

Content

The dataset is collected from Niche and each individual data is publically available. Below is the overall dataset stats - # total records = 712, 107 # total places = 56, 800

Some insight about data: # guid Generated by Niche and unique to place/entity. # body Actual review data. # rating Rating on a scale of 0 to 5. # author Provider of the review/rating. (aka Niche user) # created Timestamp. # categories Experience type (about the entity).

Acknowledgements

All rights reserved to Niche and the user who spent valuable time providing reviewers-ratings.

Inspiration

• Can you predict a rating for reviews which has no rating?
• Use transfer learning in predicting review sentiment on another domain.
• Predict review usefulness/quality or impactful review.

Citation

If you intend to use this dataset, please cite the following - @misc{enam biswas_2021, title={Place Review Dataset - Niche (USA)}, url={https://www.kaggle.com/dsv/1842046}, DOI={10.34740/KAGGLE/DSV/1842046}, publisher={Kaggle}, author={Enam Biswas}, year={2021} } Please feel free to contact - Enam Biswas if you have any kind of questions.

Other datasets by me

• IMDb Largest Review Dataset - Over 5.5M reviews/ 1.2M spoilers.
• Bangla Largest Newspaper Dataset - Almost 1.7M Bangla news articles.

Ecologists have traditionally studied intraspecific variation by sampling species across their geographic ranges. However, whether this classic approach produces samples that accurately represent species' climatic niches is largely unknown. Alternative, niche-based study designs using species' climatic niches to inform sampling locations should more efficiently and completely capture the breadth of the niche, but the magnitude of this difference and how it may vary is unclear. Here we use conifers as a model system to explore these issues and reach specific recommendations for future sampling designs. Using an independent dataset of high-quality species' occurrences, we first show that recent publications examining variation across geographic space do a poor job of capturing the full breadth of species' niches, such that on average, only 22% of species' niche space was sampled. This was also true of a large compiled database, the International Tree-Ring Data Bank (ITRDB), which yielded average niche coverage of only 45%. Finally, we simulated common sampling designs (i.e., random points, grids, and transects) in both geographic and niche-based sampling frameworks. Using two sampling metrics, niche coverage and niche undersampling, we measured how completely and evenly these simulated studies characterized the niches of 64 North American conifers. Niche-based sampling better represented species' niches than geographic sampling, with the magnitude of this difference depending on study design and sample size. Niche-based gridded study designs achieved the most complete sampling at all but the smallest sample sizes, covering ~15-25% more of a species' niche than similar designs implemented geographically. With fewer than 10 samples, however, all study designs performed poorly, and niche-based transects achieved slightly higher niche coverage. Consequently, when more than a handful of samples are collected, we recommend that studies seeking to characterize variation across a species' niche consider using a gridded study design implemented in a niche-based sampling framework.

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Competition is assumed to shape niche widths, affecting species survival and coexistence. Expectedly, high interspecific competition will reduce population niche widths, whereas high intraspecific competition will do the opposite. Here we test in situ how intra- and interspecific competition affects trophic resource use and the individual and population niche widths of two lacustrine fish species, Arctic charr and brown trout, covering a 40 year study period with highly contrasting competitive impacts prior to and following a large-scale fish culling experiment. Initially, an overcrowded Arctic charr population dominated the study system, with brown trout being nearly absent. The culling experiment reduced the littoral Arctic charr density by 80%, whereupon brown trout gradually increased its density in the system. Thus, over the study period, the Arctic charr population went from high to low intraspecific competition, followed by increasing interspecific competition with brown trout. A...

aAll sample sizes reflect the total number of georeferenced specimens or observations available at time of data acquisition, including multiple specimens or observations at a given site. Sample sizes are restricted to North America.bAll band and encounter records obtained through written permission from the USGS Bird Banding Lab (http://www.pwrc.usgs.gov/bbl/homepage/datarequest.cfm).cObtained from the USGS North American Breeding Bird Survey (http://www.pwrc.usgs.gov/bbs/RawData/Choose-Method.cfm).dObtained from the Christmas Bird Count database project (http://infohost.nmt.edu/~shipman/z/cbc/homepage.html).eAll observational data from the Cornell Lab of Ornithology were obtained from the Avian Knowledge Network (http://www.avianknowledge.net/content).

Data from: Trees have overlapping potential niches that extend beyond their realized niches

https://doi.org/10.5061/dryad.0cfxpnw9f

This dataset includes records of tree occurrences for 188 temperate tree species of North America and associated climate data and geographical coordinates (latitude/longitude).

It also includes records of tree occurrences in arboreta around the world obtained from Botanic Gardens Conservation International (BGCI). The terms of conditions to use this data prevent us from publishing the geographical coordinates of the occurrences so these are scrubbed from the data set, although the climate data are included so that the results can be reproduced.

Data file structure

The occurrences.csv file includes records of species occurrences and climate data. Fields include:

species – Latin binomial

bio1 – mean annual temperature, degrees C

bio5 – maximum temperature of the warmest month, degrees C

bio6 – minimum ...

A major goal of community ecology is understanding the processes responsible for generating biodiversity patterns along spatial and environmental gradients. In stream ecosystems, system specific conceptual frameworks have dominated research describing biodiversity change along longitudinal gradients of river networks. However, support for these conceptual frameworks has been mixed, mainly applicable to specific stream ecosystems and biomes, and these frameworks have placed less emphasis on general mechanisms driving biodiversity patterns. Rethinking biodiversity patterns and processes in stream ecosystems with a focus on the overarching mechanisms common across ecosystems will provide a more holistic understanding of why biodiversity patterns vary along river networks. In this study, we apply the Theory of Ecological Communities (TEC) conceptual framework to stream ecosystems to focus explicitly on the core ecological processes structuring communities: dispersal, speciation, niche selection, and ecological drift. Using a unique case study from high elevation networks of connected lakes and streams, we sampled stream invertebrate communities in the Sierra Nevada, CA to test established stream ecology frameworks and compared them to the TEC framework. Local diversity increased and β-diversity decreased moving downstream from the headwaters, consistent with the river continuum concept and the small but mighty framework of mountain stream biodiversity. Local diversity was also structured by distance below upstream lakes, where diversity increased with distance below upstream lakes, in support of the serial discontinuity concept. Despite some support for the biodiversity patterns predicted from the stream ecology frameworks, no single framework was fully supported, suggesting “context dependence”. By framing our results under the TEC, we found species diversity was structured by niche selection, where local diversity was highest in environmentally favorable sites. Local diversity was also highest in sites with small community sizes, countering predicted effects of ecological drift. Moreover, higher β-diversity in the headwaters was influenced by dispersal and niche selection, where environmentally harsh and spatially isolated sites exhibit higher community variation. Taken together our results suggest that combining system specific ecological frameworks with the TEC provides a powerful approach for inferring the mechanisms driving biodiversity patterns and provides a path toward generalization of biodiversity research across ecosystems. Methods Study Area The study area was located in the Sierra Nevada Mountains of eastern California (USA) and encompasses portions of Inyo National Forest and Sequoia-Kings Canyon National Park. Over the ice-free seasons (June-September), we sampled five distinct lake-stream networks, where each network was within a spatially distinct catchment and were treated as independent replicate systems (Fig. 3). The Kern (n=24) and Bubbs (n=26) networks were sampled in 2011, the Evolution (n=21) and Cascades (n=11) networks in 2018, and Rock Creek (n=36) in 2019. For each lake-stream network, streams were sampled throughout the network along a spatial gradient from headwaters downstream as well as along a spatial gradient downstream from lakes. Because the spatial distances of the river networks and the distance separating lakes naturally vary among networks as well as backcountry sampling constraints, the number of sites sampled along the distance from headwaters gradient varied (n=11 to n=36) and the downstream lake gradient varied (n=1 to n=9). This field system and the data collected naturally provide spatial gradients relevant to test stream ecology theories. In addition, this data is ideal for testing TEC processes because of the naturally varying gradients of community size, connectivity, and environmental heterogeneity present in our sampling design. Field Methods At each sampling location, we established transects in riffle sections of streams. At five equally spaced points along transects we measured stream depth and current velocity at mid-depth using a portable flow meter (Marsh-McBirney Flow Mate 2000). We then calculated stream discharge as the sum of the product of average depth x current velocity x width/5 over all transect points (Gordon et al. 2010; Herbst et al. 2018). A calibrated YSI multiparameter device was placed above transects to measure temperature, dissolved oxygen, conductivity, and pH. Benthic chlorophyll data was collected by scrubbing the entire surface area of three randomly selected cobble sized rocks (64-255 mm) of benthic algae (periphyton) with a toothbrush for 60 seconds (Herbst and Cooper 2010). Chlorophyll measurements were taken using a handheld fluorometer (Turner Designs Aquafluor), which measures raw fluorescence units. Florescent measurements were calibrated to chlorophyll concentration using a known concentration of Rhodamine. We standardized chlorophyll measurements by accounting for both the surface area of rocks and volume of water used to remove algae. Eight to twelve macroinvertebrate samples at each site were collected using a D-frame kick net (250 mm mesh, 30cm opening, 0.09m2 sample area) in riffle habitats, depending on the density of macroinvertebrate samples collected. We took samples by placing the net on the streambed, then turning and brushing all substrate by hand in the sampling area (30cm x 30cm) immediately above the net, with dislodged invertebrates being carried by currents into the net. All macroinvertebrate samples were preserved in 75% ethanol within 48 hours of sampling. Samples were sorted, identified, and counted in the laboratory. Taxa were identified to the finest taxonomic level possible, usually to genus or species for insects (excluding Chironomidae) and order or class for non-insects (Merritt, Cummins, and Berg 2019). The replicate samples taken at each site were pooled together and divided by the number of replicates and the area sampled to determine the density of invertebrate communities. Spatial Data Stream distance measurements were taken using the R package “riverdist”, which utilizes data from the USGS National Hydrological Dataset Flowline in order to determine pairwise distances from sampling sites along the river network (Tyers 2020). We determined distance below upstream lakes, with the closest upstream lake location being the outlet of the lake determined by the USGS Watershed Boundary Dataset. For sites where multiple upstream lakes were draining into streams, we defined the upstream lake as the closest upstream lake to sites that was also along the mainstem of the flowline. We determined distance from headwaters as the streamwise distance from sites to the uppermost portion (headwaters) of the mainstem of streams, where the headwaters of streams was determined by the endpoint (beginning) of the flowline in the USGS NHD Flowline Dataset (U.S. Geological Survey 2016). In cases where multiple headwater stream reaches corresponded to downstream sites, we defined the headwaters as the particular reach that accounted for the most discharge which was determined using USGS Flowline Dataset. Upstream lake area and perimeter measurements were determined using the USGS Watershed Boundary Dataset. Land-cover proportions were computed using the 2016 USGS National Land Cover Database (Jin et al. 2019).

Code to reproduce the analyses from: Dallas,T, and C Ten Caten. 2025. Linking geographic distribution and niche through estimation of niche density. Journal of Animal Ecology. Code is written in R and the file is in R markdown (.Rmd). The Rdata file included (env.RData) contains the environmental data layers used, but code to recreate these layers is also included in the analysis.Rmd (keep in mind that it will take some time and processing power). redlist_simple_summary.csv is the information from the IUCN redlist used in Appendix S1 of the manuscript. sessionInfo() for the R workspace is below for transparency and hopefully reproducibility (we recognize that some code will require modification in the future, as some spatial packages used here are being replaced by others).{r}sessionInfo()R version 4.4.2 (2024-10-31)Platform: x86_64-pc-linux-gnuRunning under: Ubuntu 22.04.5 LTSMatrix products: defaultBLAS: /usr/lib/x86_64-linux-gnu/atlas/libblas.so.3.10.3 LAPACK: /usr/lib/x86_64-linux-gnu/atlas/liblapack.so.3.10.3; LAPACK version 3.10.0locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C time zone: America/New_Yorktzcode source: system (glibc)attached base packages:[1] stats graphics grDevices utils datasets methods base other attached packages: [1] RColorBrewer_1.1-3 ggplot2_3.5.1 ape_5.8 [4] alphahull_2.5 rnaturalearthdata_0.1.0 countrycode_1.5.0 [7] CoordinateCleaner_2.0-20 terra_1.7-39 raster_3.6-23 [10] sp_2.1-4 geosphere_1.5-20 geometry_0.4.7 [13] dbplyr_2.5.0 gbifdb_0.1.2 dplyr_1.1.4 [16] plyr_1.8.9 loaded via a namespace (and not attached): [1] tidyselect_1.2.1 farver_2.1.2 arrow_12.0.1 [4] R.utils_2.12.3 sgeostat_1.0-27 lazyeval_0.2.2 [7] spatstat.geom_3.2-9 digest_0.6.37 lifecycle_1.0.4 [10] sf_1.0-13 spatstat.data_3.0-4 magrittr_2.0.3 [13] compiler_4.4.2 rlang_1.1.4 tools_4.4.2 [16] utf8_1.2.4 data.table_1.16.2 labeling_0.4.3 [19] bit_4.5.0 interp_1.1-4 classInt_0.4-9 [22] xml2_1.3.6 abind_1.4-5 KernSmooth_2.23-24 [25] withr_3.0.2 purrr_1.0.2 R.oo_1.26.0 [28] grid_4.4.2 polyclip_1.10-6 fansi_1.0.6 [31] e1071_1.7-16 colorspace_2.1-1 scales_1.3.0 [34] spatstat.utils_3.0-4 cli_3.6.3 crayon_1.5.3 [37] generics_0.1.3 rgbif_3.7.7 httr_1.4.7 [40] magic_1.6-1 DBI_1.2.3 proxy_0.4-27 [43] stringr_1.5.1 parallel_4.4.2 rnaturalearth_0.3.3 [46] assertthat_0.2.1 vctrs_0.6.5 Matrix_1.7-1 [49] jsonlite_1.8.9 bit64_4.5.2 hexbin_1.28.4 [52] units_0.8-2 splancs_2.01-44 rgdal_1.6-7 [55] glue_1.8.0 spatstat.random_3.2-3 codetools_0.2-19 [58] stringi_1.8.4 gtable_0.3.6 deldir_1.0-9 [61] munsell_0.5.1 tibble_3.2.1 pillar_1.9.0 [64] R6_2.5.1 oai_0.4.0 lattice_0.22-5 [67] R.methodsS3_1.8.2 class_7.3-22 Rcpp_1.0.13-1 [70] nlme_3.1-165 whisker_0.4.1 rgeos_0.6-3 [73] pkgconfig_2.0.3

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...

This dataset provides the variables used for the analyses of the corresponding study. These variables are derivative products from the raw dataset of ABMI found here: https://www.abmi.ca/home/data-analytics/da-top/da-product-overview/Species-Habitat-Data.html. This dataset allows to replicate the analyses of the study. However, note that some data are accessible only through a data sharing agreement with ABMI. See the readme document for more details on how to obtain assess to these data.

Description of the columns of the dataset:

Latitude: Latitude of the sites (corresponding to ABMI grid, exact locations are unknown)
Longitude: Longitude of the sites (corresponding to ABMI grid, exact locations are unknown)
Protocol: Sites sampled under the Terrestrial or the Wetland protocol (see below)
Site: ABMI unique ID for each site
Year: Year of sampling
Richness_observed: Calculated vascular plant richness (see below for access to raw data)
Richness_Chao: Calculated Chao richness (...

1. Species absent from a community, but with the potential to establish (dark diversity) are an important, yet rarely considered, component of habitat specific species pools. However, quantifying this component remains a challenge as dark diversity cannot be observed directly, and must be estimated. Here, we empirically test whether species ecological requirements or species co-occurrences provide accurate estimates of dark diversity. 2. We used two spatially nested independent datasets, one comprising 3033 samples of coastal grassland vegetation plots of 4m2 and 200m2 from Scotland, UK and another comprising 780 samples of forest vegetation plots of 30m2 and 500m2 from Switzerland. Dark diversity for each of the smaller scaled plots was estimated through investigating the degree of 1) similarity in ecological requirements (measured as Ellenberg values) and 2) co-occurrence likelihood of all species observed. Estimates were validated through comparing estimates with observed species at ...

To examine the potential effect of an invasive coccinellid (Harmonia axyridis) on the resident community of coccinellids, we sampled predators and prey associated with organic Brassica oleracea production on 6 farms during 2 years in the Distrito Federal, Brasil and conducted a food acceptability trial to estimate niche breadth and overlap among the coccinellids. The data are in two files. The first is a community sample data set, with columns describing the sample characteristics (year, farm, sample period) and the summed counts of all macroinvertebrates found on 30 plants at each sample period, farm and year. There are 120 samples and 36 populations of macroinvertebrates in the data set. The second data set is the acceptability of 4 aphid prey species to 3 stages of 4 species of coccinellids. There are 15 replicates of the 48 treatments. The data also include the biomass of the predators at the end of the experiment. Farms have been de-identified, and the data can be used by anyone wi...

Explaining macroevolution from microevolution is a key issue in contemporary evolutionary theory. A recurrent macroevolutionary pattern is that some niche‐related traits consistently evolve slower than others, so called niche conservatism. Despite a growing amount of data, the underlying evolutionary processes are not fully understood. I here analyse adaptive radiations in an individual‐based eco‐evolutionary model. I find a coevolutionary mechanism – evolutionary niche monopolisation – as a possibly important generator of niche conservatism. A single lineage of a radiating clade can monopolise, and later diversify within, a substantial part of the available niche space – much larger than what can be explained by limiting similarity. This leads to niche conservatism, since no species evolves into or out of the monopolised region. The region can in this sense also be described as an adaptive zone. The model indicates that evolutionary niche monopolisation is operative in a large part of parameter space, underlining its possible importance. The mechanism is driven by competitive interactions and differences in niche widths in alternative niche dimensions. I discuss plausible examples of evolutionary niche monopolisation in well‐studied natural systems.

Models of species ecological niches and geographic distributions now represent a widely used tool in ecology, evolution, and biogeography. However, the very common situation of species with few available occurrence localities presents major challenges for such modeling techniques, in particular regarding model complexity and evaluation. Here, we summarize the state of the field regarding these issues and provide a worked example using the technique Maxent for a small mammal endemic to Madagascar (the nesomyine rodent Eliurus majori). Two relevant model-selection approaches exist in the literature (information criteria, specifically AICc; and performance predicting withheld data, via a jackknife), but AICc is not strictly applicable to machine-learning algorithms like Maxent. We compare models chosen under each selection approach with those corresponding to Maxent default settings, both with and without spatial filtering of occurrence records to reduce the effects of sampling bias. Both selection approaches chose simpler models than those made using default settings. Furthermore, the approaches converged on a similar answer when sampling bias was taken into account, but differed markedly with the unfiltered occurrence data. Specifically, for that dataset, the models selected by AICc had substantially fewer parameters than those identified by performance on withheld data. Based on our knowledge of the study species, models chosen under both AICc and withheld-data-selection showed higher ecological plausibility when combined with spatial filtering. The results for this species intimate that AICc may consistently select models with fewer parameters and be more robust to sampling bias. To test these hypotheses and reach general conclusions, comprehensive research should be undertaken with a wide variety of real and simulated species. Meanwhile, we recommend that researchers assess the critical yet underappreciated issue of model complexity both via information criteria and performance on withheld data, comparing the results between the two approaches and taking into account ecological plausibility.

The adaptability of species’ climatic niches can influence the dynamics of colonisation and gene flow across climatic gradients, potentially increasing the likelihood of speciation, or reducing extinction in the face of environmental change. However, previous comparative studies have tested these ideas using geographically, taxonomically and ecologically restricted samples, yielding mixed results, and thus the processes linking climatic niche evolution with diversification remain poorly understood. Focusing on birds, the largest and most widespread class of terrestrial vertebrates, we test whether variation in species diversification among clades is correlated with rates of climatic niche evolution, and the extent to which these patterns are modified by underlying gradients in biogeography and species’ ecology. We quantified climatic niches, latitudinal distribution and ecological traits for 7657 (~75%) bird species based on geographical range polygons, and then used Bayesian phylogenet...

phyloeny matching datasetBased on the published DaPhNe plant phylogeny (Durka & Michalski 2012 Ecology), trimmed to plants within present food web dataset (2587 taxa). Missing taxa added (113) as described in manuscript. Phylogeny is in newick format.German Phyl trimmed to AltPea dataset.trePearse_Altermatt2015-R code for DryadR code with general functions for host use models and predictions. Appended at the end of the file is specific code for the manuscript.

Niche variation at population level mediates niche packing (i.e., patterns of species’ spread within the niche space) and species coexistence at community level. Competition and ecological opportunity (resource diversity) are two of the main mechanisms underlying niche variation. Dense niche packing could occur through increased niche partitioning or increased niche overlap. In this study we used stable carbon and nitrogen isotope data of 635 individual rodents from 4 species across 9 sites in the montane region of a subtropical island to test the effects of competition and ecological opportunity on population isotope niche size, inter-individual niche difference within population, and inter-specific niche overlap within community. We used the Bayesian Standard Ellipse Area (SEAB, the ellipse area enclosed by carbon and nitrogen isotope values of organisms on a bi-plot) to estimate population niche size and inter-specific niche overlap. Inter-individual niche difference within population was quantified as isotopic divergence and isotopic uniqueness. We used rodent abundance (the number of unique individuals captured) to measure competition and plant isotope niche size (plant SEAB) to measure ecological opportunity. The rodents experienced competition as evidenced by a negative relationship between population change rate and conspecific abundance. Rodent population niche size increased with ecological opportunity but not competition. The inter-individual niche difference (isotopic uniqueness) increased with competition (inter-specific competition only) but not ecological opportunity. At community level, inter-specific niche overlap (herbivore—omnivore pair only) increased with competition (the combined abundance of the pair) but not ecological opportunity. This study demonstrated that isotope niche variation of the rodents could be hierarchically influenced by ecological opportunity and competition, with the former setting the limit of population niche size across communities and the latter shaping inter-individual niche difference and inter-specific niche overlap within communities. Under strong intra-specific competition and limited ecological opportunity for niche expansion, individuals may choose to increase their isotopic uniqueness from conspecifics at the cost of overlapping with heterospecifics of different trophic roles within the community niche space as overall competition increases. Denser niche packing of these rodent communities might be achieved through increased niche overlap. This dataset contain stable carbon and nitorgen isotope data of rodents and plants collrected from a total of 9 sites spanning 1800-3000 m in altitude in Taiwan. All sites are mainly composed of forests, with varying degrees of shrublands, grasslands and/or farmlands mixed in. The data file included two worksheets. The first worksheet contained stable isotope values of hair samples from 4 rodent species (Alexandromys kikuchii, Apodemus semotus, Eothenomys melanogaster, Niviventer culturatus; same species could be represented at more than one site), and the second contained stable isotope values of foliar samples from 92 species (the number of plant species sampled ranged from 10 to 25 across the 9 sites; same species could be represented at more than one site). We collected a small amount of hair from the lower back each adult rodent. We used only one hair sample from each unique individual. There was no distinct seasonal molting in these rodents. Adult hair therefore is likely replaced as needed, and may reflect diet incorporated over a few months. We obtained plant foliar isotopic values from literature (site WL; see related works) and samples of the common plant species collected at each site opportunistically during rodent trapping (one foliar sample per plant species). Rodent hair samples were lipid-extracted in 2:1 chloroform:methanol solution for 24 hours, rinsed with distilled water, and oven-dried at 55°C for 24-48 hours. Approximately 1±0.2 mg of the hair tissue were loaded into tin capsules for isotope analysis. The plant foliar samples were rinsed with distilled water, oven-dried at 55°C for 48-72 hours, and grounded into find powder. Approximately 3 mg of plant foliar samples were loaded into tin capsules for isotope analysis. Stable carbon and nitrogen isotope analysis was performed at UC Davis Stable Isotope Facility (ThermoFinnigan Delta Plus, Bremen, Germany). The mean isotope values of the plants at each site should be subtracted from rodent hair values if cross-site comparision of rodent isotope niche is to be compared.

This repository contains the code and data to reproduce the analyses in :

Ten Caten, C., Holian, L., Dallas, T. "Effects of occupancy estimation on abundance-occupancy relationships"

In the Data.rar file we provide the datasets needed to run the code. The file MammalsData.RData contains the exact NEON small-mammal data used in our analyses. Thus, instead of using the function loadByProduct to download the data (line 36) from the NEON database (might take some time), the user can run line 38 and skip that part.

The second chunk of code download occurrence data for the species found in the NEON dataset from GBIF database. That chunk of code might also take a while to run, so we provide the final product (MammalsOccNEON.txt) that can be imported in line 201 so that chunk doesn't need to be run.

The third chunk of code create the spatial poligons for the species geographic range. We also provide these poligons (MammalsHull.RData) that can be loaded by running line 242 instead of running the entire code. Notice that if the poligons are imported, lines 207-213 in the third chunk will still needed to be run in order to name each poligon so that the rest of the code runs smoothly.

Repository for "Morphological evolution and niche conservatism across a continental radiation of Australian blindsnakes"

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These data scripts were used to perform analyses included in the research paper "Morphological evolution and niche conservatism across a continental radiation of Australian blindsnakes"

Main questions for the study:

1. What are the main axes of morphological variation?
2. Does variation in morphology among species correlate with their current environments?
3. Are lineages that occupy ecologically similar habitats morphologically convergent?
4. Is speciation predominantly allopatric or sympatric?
5. Do sister species have greater morphological and ecological niche overlap than expected relative to non-sister species pairs?

## Data structure

Contents in the data folder is archived as a zip and can be downloaded from Zenodo (for all versions see https://zenodo.org/doi/10.5281/zenodo.10397830). Once you unzip the zipped files, you will see three folders and some files that are no in any folders.

/data/ - files that were manually created and the phylogeny

/data/script_generated_data/ - A combination of processed data needed to run the analyses

/data/dorsal/ - photographs of the head from the dorsal view. These photos were used for digitising landmarks and semilandmarks.

/data/worldclim2_30s/ - cropped and merged annual temperature from WorldClim2 (Fick and Hijmans 2017), soil bulk density from Soil and Landscape Grid of Australia, and Global Aridity Index from Zomer et al. (2022).

/DREaD/ - contains some files required to replicate DREaD analysis

## Code/Software

All scripts can be run using open source software. Scripts should be run in order to create necessary files that will be saved in /data/script_generated_data/ for further scripts. R is required to run R scripts (.R).

### /Code

- utility/*.R - scripts for custom functions. These are sourced in other scripts.
- DREaD/*.R - scripts associated with DREaD analyses
- 00_linear_measurement_shaperatio.R - script used to account for sexual dimorphism and calculate conventional PCA. Addresses Q1.
- 01_model_fitting.R - script used to address Q2 and plot visualisations.
- 02_convergence.R - this script calculates Ct1-4 and C5 scores. Addresses Q3.
- 02_convergence_model_fitting.R - this script evaluates fit of different evolutionary models to traits. Addresses Q3.
- 02_convergence_test_simulations.R - simulation studies to show that our phylogeny has sufficient power to detect convergence.
- 03_niche_enmtools_bias_account.R - calculates ecological niche models (ENMs) for each species using MAXENT. Runs Age-Overlap Correlation tests for geography and ENMs. Partially addresses Q4.
- 03_DREaD_Blindsnakes_AS.R - script to run DREaD analysis.
- 03_morpho_niche_overlap_plots.R - Runs Age-Overlap Correlation tests for body shape and snout shape. Plots AOCs. Partially addresses Q4.
- 04_pairwise_distance_test.R - Binomial tests between sister and non-sister pairs for ENMs and Geographic Range. Partially addresses Q5
- 04_morpho_pairwise.R - Binomial tests between sister and non-sister pairs for body shape and snout shape. Partially addresses Q5

## Contact

Should you have questions about these scripts or would like to request raw data, please do not hesitate to contact Sarin Tiatragul (contact information can be found in the paper) or on Github (https://github.com/stiatragul/blindsnakemorphoevo)

## References

Fick, S. E., and R. J. Hijmans. 2017. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37:4302–4315.

Zomer, R. J., J. Xu, and A. Trabucco. 2022. Version 3 of the global aridity index and potential evapotranspiration database. Scientific Data 9:409.

Consideration of the properties of the sources of selection potentially helps biologists to account for variation in selection. Here we explore how the variability of natural selection is affected by organisms that regulate the experienced environment through their activities (whether by constructing components of their local environments such as nests, burrows, or pupal cases, or by choosing suitable resources). Specifically, we test the prediction that organism-constructed sources of selection that buffer environmental variation will result in reduced variation in selection gradients, including reduced variation between (i) years (temporal variation), and (ii) locations (spatial variation), and (iii) weaker directional selection, relative to non-constructed sources. Using compiled datasets of 1045 temporally replicated, 257 spatially replicated, and a pooled dataset of 1230 selection gradients, we find compelling evidence for reduced temporal variation and weaker selection, in response to constructed compared to non-constructed sources, and some evidence for reduced spatial variation in selection. These findings, which remained robust to alternative datasets, taxa, analytical methods, definitions of constructed/non-constructed, and other tests of reliability, suggest that organism-manufactured or chosen components of environments may have qualitatively different properties from other environmental features.